A Prediction-based Dynamic Resource Management Approach for Network Virtualization

被引:0
|
作者
Li, Jiacong [1 ]
Wang, Ying [1 ]
Wu, Zhanwei [1 ]
Feng, Sixiang [1 ]
Qiu, Xuesong [1 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
network virtualization; prediction-based resource management; double exponential smoothing;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
in network virtualization environment, multiple virtual networks share the same resource of a physical network. Since the physical resources of a substrate network is limited, it is necessary to improve the utilization of physical resources. Considering the resource requirement of a virtual network may change over its lifetime, we propose a prediction-based resource management mechanism. To increase the utilization of the substrate network, we can adjust the resource allocated to the virtual network based on the result of prediction. Additionally, in order to avoid the result of prediction deviates from the real requirement, we compare our prediction result with the collection of the resource utilization at real time to ensure the correctness of our result. The simulation results show that our approach can increase the utilization of the physical resource and improve the virtual network acceptance ratio while ensuring the requirement of the virtual networks.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Prediction-based Resource Slicing for Service Level Agreement Guarantee: A Deep Learning Approach
    Gao, Shengyu
    Zhang, Heng
    Shi, Zuoqiao
    Sun, Yanzan
    Zhang, Shunqing
    Chen, Xiaojing
    [J]. 2022 31ST WIRELESS AND OPTICAL COMMUNICATIONS CONFERENCE (WOCC), 2022, : 68 - 73
  • [32] Machine Learning for Dynamic Resource Allocation in Network Function Virtualization
    Schneider, Stefan
    Satheeschandran, Narayanan Puthenpurayil
    Peuster, Manuel
    Karl, Holger
    [J]. PROCEEDINGS OF THE 2020 6TH IEEE CONFERENCE ON NETWORK SOFTWARIZATION (NETSOFT 2020): BRIDGING THE GAP BETWEEN AI AND NETWORK SOFTWARIZATION, 2020, : 122 - 130
  • [33] Prediction-based Instant Resource Provisioning for Cloud Applications
    Khatua, Sunirmal
    Manna, Moumita Mitra
    Mukherjee, Nandini
    [J]. 2014 IEEE/ACM 7TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC), 2014, : 597 - 602
  • [34] Prediction-based dynamic bandwidth allocation in WiFi
    Feng, HF
    Shu, YT
    Yang, OWW
    Wang, H
    [J]. PERFORMANCE, QUALITY OF SERVICE, AND CONTROL OF NEXT-GENERATION COMMUNICATION NETWORKS II, 2004, 5598 : 246 - 253
  • [35] Prediction-Based Partitions Evaluation Algorithm for Resource Allocation
    Pupykina, Anna
    Agosta, Giovanni
    [J]. PARALLEL COMPUTING: TECHNOLOGY TRENDS, 2020, 36 : 364 - 375
  • [36] Prediction-based resource allocation for OFDM in wireless channels
    Prince, Kamau
    Krongold, Brian
    Dey, Subhrakanti
    [J]. 6TH AUSTRALIAN COMMUNICATIONS THEORY WORKSHOP 2005, PROCEEDINGS, 2005, : 260 - 265
  • [37] Prediction-based relaxation solution approach for the fixed charge network flow problem
    Zhang, Weili
    Nicholson, Charles D.
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2016, 99 : 106 - 111
  • [38] Mobility prediction-based wireless resource allocation and reservation
    Yang, X
    Chen, QB
    Mao, YJ
    Long, KP
    Ma, B
    [J]. CONTENT COMPUTING, PROCEEDINGS, 2004, 3309 : 1 - 11
  • [39] Performance of prediction-based dynamic bandwidth provisioning
    Wang, H
    Huang, CS
    Yan, J
    [J]. Performance Challenges for Efficient Next Generation Networks, Vols 6A-6C, 2005, 6A-6C : 959 - 968
  • [40] A Connectionist Approach to Dynamic Resource Management for Virtualised Network Functions
    Mijumbi, Rashid
    Hasija, Sidhant
    Davy, Steven
    Davy, Alan
    Jennings, Brendan
    Boutaba, Raouf
    [J]. 2016 12TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT AND WORKSHOPS(CNSM 2016), 2016, : 1 - 9